In recent years, the technology for compressing a still image or a moving image has been remarkably progressing. Such a compressing technology is widely used for recording or reproducing images in or from recording media such as optical disks, hard disks, or solid-state memories, and for transmitting images through communication channels such as the Internet. It is also used in the field of broadcasting. As a method for compressing a still image, Joint Photographic Experts Group (JPEG) method is well known, and as a method for compressing a moving image, Moving Picture Experts Group (MPEG) method is well known. Other than these, a variety of methods have been proposed and put to practical use.
It is known that, during a coding/decoding process for compressing/decompressing image data, a variety of noises which are not in the original image are generated. Block noise and mosquito noise are typical noises. Block noise is caused by the operation of compressing data in which one frame of image is divided into plural areas or blocks to process each block independently, and generated near the boundaries of the blocks. Mosquito noise is caused in the process of compression in which the image data is frequency-resolved by the discrete cosine transform (DCT) and the high-frequency components are removed. In the Fourier analysis, this kind of noise generation is generally called the Gibbs phenomenon. Both of these noises become more noticeable as the compression ratio is increased in order to enhance the recording or transmission efficiencies. Hence, conventionally, a variety of methods for removing or minimizing such noises have been studied and developed (for example, refer to Patent Documents 1 and 2, and other documents).
Removing visually unpleasant and annoying noises as previously described is one of the very important techniques both in processing a still image and in processing a moving image. However, if the noise removal effect is increased to enhance the image quality, a part of the image information which is not a noise but essentially needed may be lost, possibly making the image unnatural and unattractive. In general, performing an advanced noise removal complicates the process and increases the circuit size. This brings about a problem of a rise in the cost and an increase in the size of the circuit board.
Over the years, the inventors of the present patent application have been conducting research on the attempt, particularly in the field of digital audio, to introduce the sampled-data control theory capable of handling the continuous-time feature, more specifically, sampled-data H∞ control, into the digital/analog (D/A) conversion technology, sampling rate conversion technology, and other technologies which handle digital audio signals (refer to Patent Documents 3 and 4, and other documents). This technology aims at optimizing or nearly optimizing the acoustic sound quality as an analog audio by designing the digital filter for the D/A conversion or sampling rate conversion, not only by considering the sample of an original digital signal as a simple discrete-time signal but also by taking the analog frequency characteristics included in the response among samples into account.
In other words, the aforementioned filtering technology is an attempt to pursue the natural sound which is as close to the original analog audio as possible, under the limitations of a predetermined sampling frequency and quantization bit rate. This filter, which is called the “YY filter,” has been put to practical use in integrated circuits (ICs) for mobile phones and portable music players, and in other devices.
In view of the progress of the image compression technology in recent years as described earlier and the need for improving the picture quality associated therewith, the inventors of the present patent application have been pursuing the attempt to apply the sampled-data H∞ optimization method which is the basics of the aforementioned technology to removing an image noise. And they have already disclosed an example in which it is applied to remove the noise of a still image (refer to Non-Patent Document 1) and an example in which it is applied to remove the noise of a moving image (refer to Non-Patent Document 2). A study of these conventional image removal techniques confirmed that block noise could be effectively removed by applying the sampled-data H∞ optimization method to the noise removal of an image. However, the study also indicated that there were problems in that a part of information which was not originally a noise might be regarded as a noise to be removed, or inversely, a noise might be erroneously recognized as a part of image information and remains unremoved.    Patent Document 1: Japanese Unexamined Patent Application Publication No. 2005-295371    Patent Document 2: Japanese Unexamined Patent Application Publication No. 2006-140818    Patent Document 3: Japanese Unexamined Patent Application Publication No. 2001-127637    Patent Document 4: Japanese Unexamined Patent Application Publication No. 2001-358561    Non-Patent Document 1: Kakemizu, Nagahara, Kobayashi, and Yamamoto, “Noise Reduction of JPEG Images by Sampled-Data H∞ Optimal ε Filters,” SICE Annual Conference 2005, pp. 1080-1085    Non-Patent Document 2: Kobayashi, Nagahara, Yamamoto, “Noise Reduction of MPEG Videos by Sampled-Data Control Theory,” Proceedings of the 51st Annual Conference of the Institute of Systems, Control and Information Engineers, May 16, 2007